Video Event Detection Based on Over-segmented STV Regions

Wang, Jing and Xu, Zhijie (2011) Video Event Detection Based on Over-segmented STV Regions. In: 2011 IEEE International Conference on Computer Vision Workshops. IEEE, Barcelona, Spain, pp. 1464-1471. ISBN 9781467300636

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Abstract

Real-world environment introduces many variations into video recordings such as changing illumination and object dynamics. In this paper, a technique for abstracting useful spatio-temporal features from graph-based segmentation operations has been proposed. A spatio-temporal volume (STV)-based shape matching algorithm is then devised by using the intersection theory to facilitate the definition and detection of video events. To maintain system efficiency, this research has integrated an innovative feature-weight evaluation mechanism which “rewards” or “punishes” recognition outputs based on the segmentation quality. Substantial improvements on both the event “Precision” and “Recall” rate and the processing efficiency have been observed in the experiments in the project.

Item Type:	Book Chapter
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Schools:	School of Computing and Engineering School of Computing and Engineering > High-Performance Intelligent Computing > Visualisation, Interaction and Vision
Related URLs:	Author Conference Publisher Conference
Depositing User:	Jing Wang
Date Deposited:	08 Nov 2011 16:18
Last Modified:	06 Apr 2018 16:57
URI:	http://eprints.hud.ac.uk/id/eprint/11834

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